ANALISIS MODEL SPRINGATE, GROVER DAN ZMIJEWSKI SEBAGAI ALAT PREDIKSI KEBANGKRUTAN PADA PT ASURANSI JIWASRAYA
DOI:
https://doi.org/10.38076/ideijeb.v1i2.16Keywords:
Bankruptcy, Springate, Grover, Zmijewski.Abstract
This study aimed to determine the most influential prediction models that cause the potential bankruptcy of a company. This type of research was quantitative by comparing the predictions and reality of corporate bankruptcy by using the calculation of three bankruptcy prediction models: Springate, Grover, and Zmjewski. The results of the study using the Springate Score and Grover models showed the same results with a percentage of 100% in which companies in 2011 to 2017 were predicted not to go bankrupt with an S score of more than 0.862 and a G score of more than 0.01. This result was in line with the relita happened that the company was still operating until now. While the results of research using the Zmijewski model showed the results that predictions and reality were inversely proportional, where bankruptcy prediction results stated that the company went bankrupt with the calculated value above 0, but the reality was that the company was still operating today. Of the three most accurate bankruptcy prediction models, the Springate and Grover models, where predictions and reality were in line with research resultReferences
Adnan, M. A. (2000). ANALISIS TINGKAT KESEHATAN PERUiAHAAN UNTUK MEMPREDIKSI POTENSI KEBANGKRUTAN DENGAN PENDEKATAN ALTMAN iKasuspada Sepuluh Perusahaan di Indonesia]. 4(2).
Goleman, daniel; boyatzis, Richard; Mckee, A. (2019). ANALISIS KEBANGKRUTAN MODEL ALTMAN Z-SCORE DAN SPRINGATE PADA PERUSAHAAN INDUSTRI PROPERTY Hafiz. Journal of Chemical Information and Modeling, 53(9), 1689–1699. https://doi.org/10.1017/CBO9781107415324.004
Hendra, J., Pujiastuti, A., Lumanto, R., & Marga, U. P. (2019). ANALISIS LAPORAN KEUANGAN DENGAN MODEL SPRINGATE SCORE. 132–137.
Husein, M. F., & Pambekti, G. T. (2015). Precision of the models of Altman, Springate, Zmijewski, and Grover for predicting the financial distress. Journal of Economics, Business & Accountancy Ventura, 17(3), 405. https://doi.org/10.14414/jebav.v17i3.362
Kuncoro, A. W. (2011). ANALISIS KEBANGKRUTAN DENGAN METODE SPRINGATE DAN ZMIJEWSKI PADA PT.BETONJAYA MANUNGGAL Tbk PERIODE 2007-2011.
Kutum, I. (2015). Predicting the Financial Distress of Non-Banking Companies Listed on the Palestine Exchange ( PEX ). Research Journal of Finance and Accounting, 6(10), 79–84.
Rokhlinasari, S. (2016). Teori-Teori dalam Pengungkapan Informasi Coorporate Social Responsibility Perbankan. 1–11.
Sunaryo Putri, D. P. (2018). Comparison of Bankruptcy Prediction Models Analysis (Altman, Springate, Grover, Ohlson and Zmijewski) on Pt. Asuransi Harta Aman Pratama, Tbk. Economics & Accounting Journal, 1(2), 156. https://doi.org/10.32493/eaj.v1i2.y2018.p156-165
Syafitri, L., & Wijaya, T. (2014). Analisis Komparatif Dalam Memprediksi Kebangkrutan Pada Pt . Indofood Sukses. Jurusan Manajemen Keuangan, STIE MDP, Palembang, 1–14.
Syamni, G., Majid, M. S. A., & Siregar, W. V. (2018). Bankruptcy Prediction Models and Stock Prices of the Coal Mining Industry in Indonesia. Etikonomi, 17(1), 57–68. https://doi.org/10.15408/etk.v17i1.6559
Yuliastry, E. C., & Wirakusuma, M. G. (2014). Analisis Financial Distress dengan Metode Z-Score Altman, Springate, Zmijewski. Jurnal Akuntansi, 6(3), 379–389.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

This work is licensed under a Creative Commons Attribution 4.0 International License.
